class_docstr: Alpine01 objective function.
  
  The Alpine01 [1]_ global optimization problem is a multimodal minimization
  problem defined as follows:
  
  .. math::
  
      f_{\text{Alpine01}}(x) = \sum_{i=1}^{n} \lvert {x_i \sin \left( x_i
      \right) + 0.1 x_i} \rvert
  
  
  Here, :math:`n` represents the number of dimensions and :math:`x_i \in
  [-10, 10]` for :math:`i = 1, ..., n`.
  
  *Global optimum*: :math:`f(x) = 0` for :math:`x_i = 0` for
  :math:`i = 1, ..., n`
  
  .. [1] Jamil, M. & Yang, X.-S. A Literature Survey of Benchmark Functions
  For Global Optimization Problems Int. Journal of Mathematical Modelling
  and Numerical Optimisation, 2013, 4, 150-194.
code: def fun(self, x, *args):
      self.nfev += 1
  
      return sum(abs(x * sin(x) + 0.1 * x))
  
imports: from numpy import abs, cos, exp, pi, prod, sin, sqrt, sum
  from .go_benchmark import Benchmark
label_desc: Use image node_id 2 for calling the Alpine01 obj's underlying member method code with example usage: obj.fun(x) and returns: sum